Field of the Invention
The present invention concerns a method and apparatus for displaying representations of regions of interest in reconstructions of medical imaging data.
In particular, the present invention relates to a method and an apparatus for improving consistency in representation of regions of interest in different data sets obtained by different systems at different times.
Description of the Prior Art
In the medical imaging field, several imaging schemes are known. For example PET (Positron Emission Tomography) is a method for imaging a subject in 3D using an injected radio-active substance which is processed in the body, typically resulting in an image indicating one or more biological functions.
The Standardized Uptake Value (SUV) is a widely-used measure for quantifying radiotracer uptake in clinical PET scans. This value is computed from the number of counts of emission events recorded per voxel in the image reconstructed from event data captured in the PET scan. Its use is intended to provide normalization for differences in patient size and body composition, along with the dose of radiotracer injected, thereby enabling inter-study comparison, both between and within individual patients.
While raw scan data may be expressed in units of Bq/ml, SUV is calculated as:
      scan    ⁢                  ⁢          data      ⁢                                        ⁢                                      (              in        ⁢                                  ⁢        Bq        ⁢                  /                ⁢        ml            )        ×    patient    ⁢                  ⁢    mass    ⁢                  ⁢          (              in        ⁢                                  ⁢        grams            )            total    ⁢                  ⁢    injected    ⁢                  ⁢    dose    ⁢                  ⁢          (              in        ⁢                                  ⁢        Bq            )      
This is typically simplified by assuming that the patient has a density of 1 g/ml, in which case the SUV becomes dimensionless.
SUVmax is the maximum observed value of SUV within a region of interest: typically a three-dimensional volume of interest, for example a representation of a lesion.
While differences in body composition and injected dose represent one source of variation, differences in scanner hardware and reconstruction software represent others, and these are not addressed by the use of SUV.
It has been observed that a single set of raw scan data may result in differing values for SUV, and so also for SUVmax, depending on the reconstruction applied to the raw scan data. A “reconstruction”, in this context, is the treatment applied to a digital photon count to convert it into image data. Practically, it is carried out by a digital computer. For example, a low resolution reconstruction will result in significant “blurring” of the image produced, so that a small lesion may appear to have a lower SUVmax than in reality, while a larger lesion of a same SUV will appear to have a larger, and possibly correct, SUVmax. Using a higher-resolution reconstruction on the same raw data will show images with more clearly-defined edges, in turn meaning that small lesions will appear to have greater SUVmax than under the lower-resolution reconstruction. SUVmax is typically the clinically-reported result of a scan.
SUVmax is the SUV of the voxel with the highest value in the region of interest. SUVpeak is the mean SUV of a 1 cm3 sphere positioned within the region of interest so as to maximize SUVpeak. So, whereas SUVmax considers only a single voxel, SUVpeak considers a small cluster of voxels.
It is clearly undesirable for the results of the PET scan to vary according to the reconstruction applied. For example, it may be required to evaluate a patient's progress by comparing two PET scan results taken at different times on different scanners. Each may have a different reconstruction, for example because a newer scanner has a higher resolution capacity. However, the two results must be aligned, that is, made comparable.
While SUVmax and SUVpeak provide an indication of the most metabolically-active region within a lesion, other measures such as metabolic tumor volume (MTV) or total lesion glycolysis (TLG) provide an indication of the total metabolic burden of a lesion. MTV is the volume enclosed by PET-derived lesion volume and TLG is the product of the MTV and SUVmean of the delineated volume.
While MTVs have shown promise as prognostic indicators and for assessing treatment response, a barrier to their widespread adoption is their dependence on scanner hardware and reconstruction protocol used to generate the image, which inhibits reproducibility and comparability between sites.
The dependence of SUV values on scanner hardware and reconstruction protocol is well established. Its reliance on a single maximal voxel value makes SUVmax particularly sensitive to differences in noise, resolution and contrast recovery, properties that vary between scanner models and reconstruction protocols. Since MTVs are typically defined using absolute or relative SUV thresholds, these volumes are also sensitive to differences in scanner model and reconstruction protocol.
In an attempt to address this variability, the EANM procedure guidelines provide specifications for activity concentration recovery coefficients (RC), as measured for example with an NEMA NU-2 IQ phantom. RCs measure the ability of an imaging system to recover the true activity concentration ratio between regions with different activity concentrations. They are a useful indicator of clinical scanner performance, incorporating the effects of scanner resolution, sensitivity, accuracy of the various corrections performed along with the reconstruction parameters such as number of iterations and subsets, and post filter smoothing.
Using a reconstruction protocol that meets these specifications ensures the generated SUV values are harmonized and therefore comparable across scanners and sites. One limitation of this approach, however, is the requirement to use a reconstruction protocol that aligns with an RC specification achievable by the majority of scanners in clinical use. This has the potential to negate the benefits of advances in technology which improve image quality and lesion detectability.
The following prior art documents may aid an understanding of the present invention:                Boellaard R, Krak N C, Hoekstra O S, Lammertsma A a: Effects of noise, image resolution, and ROI definition on the accuracy of standard uptake values: a simulation study. J Nucl Med 2004, 45:1519-27.        Boellaard R, O'Doherty M J, Weber W a, Mottaghy F M, Lonsdale M N, Stroobants S G, Oyen W J G, Kotzerke J, Hoekstra O S, Pruim J, Marsden P K, Tatsch K, Hoekstra C J, Visser E P, Arends B, Verzijlbergen F J, Zijlstra J M, Comans E F I, Lammertsma A a, Paans A M, Willemsen A T, Beyer T, Bockisch A, Schaefer-Prokop C, Delbeke D, Baum R P, Chiti A, Krause B J: FDG PET and PET/CT: EANM procedure guidelines for tumor PET imaging: version 1.0. Eur J Nucl Med Mol Imaging 2010, 37:181-200.        Jaskowiak C J, Bianco J A, Perlman S B, Fine J P, Ct FPET, Uptake S: Influence of Reconstruction Iterations on 18 F-FDG PET/CT Standardized Uptake Values. 2005:424-428.        Kelly M D, Declerck J M: SUVref: reducing reconstruction-dependent variation in PET SUV. EJNMMI Res 2011, 1:16.        NEMA NU 2-2012 Performance Measurements of Positron Emission Tomographs. Natl Electr Manuf Assoc 2013.        Van de Wiele C, Kruse V, Smeets P, Sathekge M, Maes A: Predictive and prognostic value of metabolic tumor volume and total lesion glycolysis in solid tumours. Eur J Nucl Med Mol Imaging 2013, 40:290-301.        Wahl R L, Jacene H, Kasamon Y, Lodge M a: From RECIST to PERCIST: Evolving Considerations for PET response criteria in solid tumors. J Nucl Med 2009, 50 Suppl 1:122S-50S.        